Environ. Sci. Technol. 1996, 30, 2864-2867
Emission Factors for Ethene and Ammonia from a Tunnel Study with a Photoacoustic Trace Gas Detection System MARC A. MOECKLI, MARTIN FIERZ, AND MARKUS W. SIGRIST* Infrared Physics Laboratory, Institute of Quantum Electronics, ETH Zurich, CH-8093 Zurich, Switzerland
Introduction Ethene and ammonia are two gases of environmental interest that are emitted by traffic and other sources. Their detection requires a considerable experimental effort, especially if a good time resolution is needed. The strong absorption of these two substances at 12C16O2 laser wavelengths combined with the excellent sensitivity of the photoacoustic detection method, however, allow us to detect these gases simultaneously in the ppb range with a time resolution of few minutes. Ethene is an ubiquitous substance in plant physiology. It is reported to affect plant growth and plant sensitivity to other air pollutants (1, 2). Furthermore, it plays an important role as an ozone precursor (3). For these reasons, there is an interest to determine the ethene concentration individually in the analysis of polluted ambient air. Ammonia, although not being a highly toxic substance, contributes to the formation of photochemical smog and acid rain and is mentioned in connection with forest decline (4, 5) and global warming (6). It is known that catalytic converters, although reducing most of the toxic compounds in the exhaust stream of a car, can substantially increase the emission of ammonia (7, 8). Possible chemical reactions in three-way catalytic converters leading to increased ammonia emission are discussed in ref 9. Particularly for ammonia, the emission of a car crucially depends on many factors, e.g., on the engine type, its state of operation, the type of catalytic converter installed, and its temperature (10). On-road studies that account for the emissions of a large number of in-use vehicles are therefore indispensable to assess a realistic amount of an emitted pollutant.
Experimental Section Apparatus. During the last years, we have been developing a mobile photoacoustic trace gas detection system, which is built in a trailer and can easily be moved to different sites of interest. The system is based on a commercially available sealed-off continuous wave 12C16O2 laser, which provides about 80 transitions between 9 and 11 µm with powers up to 6 W. The air to be analyzed is continuously pumped through a resonant photoacoustic cell with a flow rate between 0.5 and 2 L/min. The laser beam is mechanically * Corresponding author e-mail address:
[email protected]; telephone: ++41/1/633'22'89; fax: ++41/1/633'10'77.
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chopped at the strongest acoustic resonance of the photoacoustic cell and consecutively passes the cell where it excites vibrational-rotational energy levels of the absorbing molecules. Through nonradiative relaxations of the excited molecules, a standing pressure wave is produced within the photoacoustic cell that can be detected with commercial microphones and lock-in technique. From the measured photoacoustic absorption spectra of ambient air, the concentrations of the different absorbing species can be calculated by fitting the ambient air spectrum with the spectra of the individual pure substances. Calibration of our system is performed with certified gas mixtures (typically 100 ppm of a compound diluted in synthetic air) that can be mixed and diluted to the ppb range with a commercial gas mixing unit. Calibration measurements with ethene, ammonia, and other compounds have been performed prior to and after the field study. Our system is fully computer-controlled and can be operated unattended during extended periods. A more detailed description can be found elsewhere (11, 12). Sampling Site and General Approach. Between June 7 and July 4, 1995, we performed air pollution measurements at the Gubrist Tunnel, a 3.2-km freeway tunnel at an altitude of 450 m in the north of Zurich, Switzerland. The tunnel has two two-lane tubes for the different traffic directions and a cross section of 48 m2. Typically 38 000 vehicles passed the tunnel every day in each direction during the measuring period. Our system was placed at the outlet of the slightly ascending (slope 1.3%) southern tube, and the air to be analyzed was pumped through a 15-m Teflon PFA tube (flow rate 0.5 L/min) that was attached 1.8 m above the road surface to the tunnel wall. Prior to being analyzed, the air passed a Teflon dust filter with a porosity of 1 µm. Replacements of the Teflon filter during the measuring campaign showed no significant influence on the determined pollutant concentrations.
Results and Discussion During a consecutive 5-day period, we operated our laser continuously on 12 selected laser lines; three of them representative for ammonia absorption, three for water vapor, two for ethene, and the others for CO2, benzene, and toluene. The spectrum of these 12 selected lines could be measured within about 10 min, thereby determining the time resolution of the derived pollutant concentrations. The Gubrist Tunnel has a built-in automatic traffic counting system that records the traffic density with a time resolution of 1 h. Individual data for the number of passenger cars and long vehicles (trucks) are available, including the average speed of the vehicles passing the tunnel. With the data from the monitored pollutant concentrations, this enabled us to calculate emission factors for the mixed fleet of vehicles passing the tunnel. Determination of the Pollutant Concentrations. Figure 1 shows a typical photoacoustic absorption spectrum of tunnel air at the 12C16O2 laser wavelengths. The significant spikes in the spectrum can easily be ascribed to ammonia (9R30, 10R06, and 10R08 laser lines), to ethene (10P14), and to water vapor (10P40, 10R20, and 9P38). The four broad absorption regions in the different laser branches indicated by four circles are mainly caused by CO2, which
S0013-936X(96)00152-6 CCC: $12.00
1996 American Chemical Society
FIGURE 1. 12C16O2 laser photoacoustic absorption spectrum of tunnel air that gives clear evidence of the presence of ammonia and ethene in the tunnel air.
is the dominant absorbing compound at these wavelengths. The significantly weaker signals at two laser lines in the 9R laser branch (around 1080 cm-1) are caused by the kinetic cooling effect (13), which results in destructive signal interference of the CO2, water vapor, and ammonia absorption. The plotted spectrum demonstrates the excellent selectivity and sensitivity of our system to ethene and ammonia. The concentrations of these substances can easily be calculated from measurements on a few characteristic laser lines that are hardly affected by the absorption of other pollutants. We achieve detection limits of 4 ppb for ethene and 2 ppb for ammonia. Besides the reliable identification of ethene and ammonia, our measurements provide a time resolution of the derived concentration profiles of a few minutes, determined by the number of lines on which measurements are performed. Since in photoacoustic spectroscopy the molecular absorption processes are detected purely acoustically, the same detection technique can be used in combination with different laser types that provide suitable wavelengths for the substances to be monitored. Examples of laboratory photoacoustic studies on multicomponent gas mixtures with different lasers are given in ref 14. In previous studies in our laboratory, we have analyzed vehicle emission with a CO laser photoacoustic system (15). Ten different hydrocarbons could be identified at ppm concentrations. Besides ethene and ammonia, other pollutants of interest such as benzene, toluene, and the xylenes also absorb strongly at the 12C16O2 laser wavelengths. Their spectra are however less pronounced than those of ethene and ammonia, and they further interfere considerably with the absorption of CO2 and water vapor. Therefore, the determination of their concentrations from 12C16O2 laser photoacoustic spectra would require a pretreatement of the tunnel air to remove CO2 and water vapor prior to the analysis. In our measurements, the air was analyzed untreated to avoid any possible influence particularly on the ammonia concentrations to be monitored. A laboratory analysis of tunnel air was performed with a gas chromatograph and yielded ethene concentrations comparable to those derived from photoacoustic data. Since CO2 shows much stronger absorption features between 4 and 5 µm than at the CO2 laser wavelengths and due to its strong absorption interference with other components of the
FIGURE 2. Concentration profiles of four air pollutants during 5 days. Plotted are the hourly mean values. Total traffic density and fraction of long vehicles are recorded at the bottom.
tunnel air, it has additionally been monitored with a commercial near-infrared absorption sensor (Gas Card from Edinburgh Sensors Ltd.). The conventionally measured data have been used for the calculation of the CO2 emission factor. Furthermore, we obtained the carbon monoxide concentrations from a commercial infrared gas analyzer (UNOR 6N). For safety reasons, CO is continuously monitored in the Gubrist Tunnel. Figure 2 shows the concentration profiles of the discussed four pollutants during 5 days. In addition, the traffic density is recorded.
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The concentration profiles are obviously correlated with the traffic density. Rather high concentrations, well above the natural background level, have been recorded for ethene and ammonia, in the latter case between 100 and 400 ppb. In clean rural air, the ammonia concentration normally varies in the low ppb and ppt range, whereas at an urban site in Yokohama, diurnal monthly average concentrations above 10 ppb during the late spring and summer months are reported (16). Van der Eerden et al. (17) defined critical levels for adverse effects of ammonia on plants. A value of 270 µg/m3 is published for exposure periods of 1 day. This corresponds to approximately 390 ppb and is of the order of the maximum ammonia concentrations measured at the tunnel outlet. In contrast to the other pollutant concentrations, the ammonia concentration stayed at rather high levels even at nighttime. This fact is most probably caused by adsorption of ammonia to the stainless steel walls of the photoacoustic cell and consecutive desorption during periods of low concentrations. Because we did not observe a drift in the ammonia concentrations during the whole measuring period, it can be assumed that this effect would only have influenced low concentration values. Air stagnation in the tunnel and desorbing effects from the tunnel walls are other possible explanations that have not been investigated in detail. Since low concentration periods are correlated with low traffic densities, they have not been taken into account in the following calculations and should therefore not have influenced the determined emission factors. Calculation of the Air Flow through the Tunnel. In the Gubrist Tunnel, the air is normally exchanged by the pure piston impact of the traffic. The installed tunnel ventilation is only used in case of a dangerously reduced visibility or of high CO levels. The basic relation to calculate the air flow through the tunnel from the traffic density is based on the work of Haerter (18). An explicit equation for the Gubrist Tunnel was derived by Steinemann (19). We have checked the validity of the equation with data from earlier air flow measurements in the Gubrist Tunnel. The total deviation of the calculated from the measured air speed for the investigated period of 1 week was less than 13.5% for 68.3% of the considered data. Calculation of the Emission Factors. Emission factors for ammonia, ethene, CO, and CO2 have been determined according to a procedure described by Steinemann (19). Due to the limited time resolution of the traffic data, we did not determine individual values for light and heavy traffic. As seen in Figure 2, the fraction of long vehicles on the total traffic stayed however below 15% during all the measuring period with an average of 4.4%. No attempt was made to characterize the vehicle fleet according to fuel type. For the calculations, only concentration values have been taken into account for which the average traffic speed exceeded 80 km/h (speed limit 100 km/h) and the air speed in the tunnel exceeded 5 m/s. The first restriction ensures that the speed differences within the traffic are not too high, which could result in an erroneous calculated air speed, whereas the second restriction allows us to neglect the impact of the meteorological pressure difference between the tunnel inlet and outlet on the air speed. Finally, it was checked that the tunnel ventilation was not in use during the sampling period to ensure that the tunnel was ventilated by the pure piston impact of the vehicles. The emission
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FIGURE 3. Pollutant concentrations versus (Gtraffic/vair)(T/p). The additional factor T/p accounts for the conversion from ppm to µg/m3, where T indicates the temperature and p is the air pressure.
factor EF of a polluant is given by (20)
EF )
∆concvairΦ FtrafficL
(1)
Here ∆conc denotes the difference of the pollutant concentration between the tunnel inlet and outlet, vair is the air speed in the tunnel, Φ is the tunnel cross section, Ftraffic is the traffic density, and L is the tunnel length. Since the pollutant concentrations could only be monitored at the tunnel outlet, it was assumed that the background concentration of a pollutant at the tunnel outlet is equal to that at the tunnel inlet. This assumption should be well justified because the average air speed in the tunnel exceeded 5 m/s for the considered data and should thus not have been diluted by outside air. By plotting the outlet concentration values versus the ratio of the traffic density and the air speed in the tunnel, the average emission factor for all vehicles results from a linear least square regression basically as the slope of the regression line. The results are shown in Figure 3 and Table 1. By relating the emission factors for ethene, ammonia, and CO to our CO2 emission factor and multiplying them with an estimated emission rate of 3.177 g of CO2/g of fuel [derived from our emission factor for CO2 and an average carbon to hydrogen ratio of the fuel (diesel and gasoline) of 1:1.85 (21)] they could be converted to a g/g of fuel basis. However, due to the somewhat speculative assumptions, data converted with this procedure have not been included in Table 1. Carbon monoxide (CO), nitric oxide (NOx), and the total hydrocarbon emission are measured on an annual basis at the Gubrist Tunnel. For the measuring period, these data were however not available. From ref 22, an emission factor for CO of 4.5 g/(vehicle‚km) can be derived for the southern
TABLE 1
Average Emission Factors for Total Vehicle Fleet Operating between 80 and 100 km/h, Calculated from Concentration Profiles and Traffic Densitya gas
emission factor (g/km)
ethene (C2H4) ammonia (NH3) carbon dioxide (CO2) carbon monoxide (CO)
0.026 ( 0.003 0.015 ( 0.004 201 ( 12 5.2 ( 0.5
a The errors quoted are the random errors given by the linear least square regression.
tube of the Gubrist Tunnel in 1994. This is about 15% lower than our result. In ref 23 an emission factor of 199.92 g/(vehicle‚km) is estimated for the CO2 emission of passenger cars on freeways in 1995 and higher values for heavy traffic. This is in excellent agreement with our data. Emission factors for ethene and ammonia are rarely found in literature. During an extended field study in the Gubrist Tunnel in 1994, Staehelin et al. (24) determined an emission factor for ethene that is in good agreement with our calculations. In ref 8, emission factors of 2-5 mg/km for ethene and of 5-20 mg/km for ammonia were determined in a test stand measurement according to the U.S. FTP-75 test for cars equipped with catalytic converters. For noncatalytic converter cars, emission factors of 50-90 mg/ km for ethene and of 4-10 mg/km for ammonia resulted in the same study. It is concluded that the ammonia emission is approximately doubled due to the impact of the catalytic converter. Generally, data determined in test stands vary considerably even within vehicles from the same manufacturer (7, 8, 25). The ammonia concentrations monitored at the Gubrist Tunnel can most probably be ascribed to the impact of the increased number of vehicles equipped with catalytic converters in Switzerland. Since 1988 when new emission regulations for traffic were introduced in Switzerland (regulation FAV 1), the number of catalytic converter cars in the district of Zurich rose from 17% to 78% in January 1996. Only a few emission factors from road traffic have been published (26, 27), to our knowledge none in Switzerland. In 1981, Pierson and Brachaczek (26) determined emission rates of 1.3 mg/km for NH3 and NH4+ for gasoline-powered vehicles and 25 mg/km for diesel-powered vehicles in a study in the Allegheny Mountain Tunnel of the Pennsylvania Turnpike. Gregori et al. (27) determined emission rates for ammonia of 5.87 and 6.95 mg/km for all vehicles on 2 days in the Tauern Tunnel (Austria) in 1988. At that time, however, vehicles with catalytic converters were not yet widespread. Based on traffic data (23) of 1995, an extrapolation with our emission factor leads to a total ammonia emission from road traffic of 700-800 t/yr in Switzerland. This corresponds to about 1% of the total ammonia emission estimated in Switzerland in 1990 (17, 28). The same percentage was ascribed to traffic in Austria in 1990 (29).
Acknowledgments We are grateful to the help provided by the Strassenverkehrsamt Zu ¨rich and the Verkehrsleitzentrale Zu ¨rich as well as to Mr. Steinemann (Ingenieurbu ¨ ro Steinemann); Ch. Keller (Seminar fu ¨ r Statistik, ETHZ); U. Beck, M. Messmer, and D. Brunner (LAPETH); V. Stadelmann (PSI); and the ATAL Zu ¨rich for their support during this study. This project
is funded by the Swiss National Science Foundation and the ETH Zu ¨ rich.
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Received for review February 19, 1996. Revised manuscript received May 21, 1996. Accepted May 28, 1996. ES960152N
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